Heterometallic cluster-based organic frameworks as highly active electrocatalysts for oxygen reduction and oxygen evolution reaction: a density functional theory study

Abstract

Recently, metal–organic frameworks are one of the potential catalytic materials for electrocatalytic applications. The oxygen reduction reaction and oxygen evolution reaction catalytic activities of heterometallic cluster-based organic frameworks are investigated using density functional theory. Firstly, the catalytic activities of heterometallic clusters are investigated. Among all heterometallic clusters, Fe₂Mn–Mn has a minimum overpotential of 0.35 V for oxygen reduction reaction, and Fe₂Co–Co possesses the smallest overpotential of 0.32 V for oxygen evolution reaction, respectively 100 and 50 mV lower than those of Pt(111) and RuO₂(110) catalysts. The analysis of the potential gap of Fe₂M clusters indicates that Fe₂Mn, Fe₂Co, and Fe₂Ni clusters possess good bifunctional catalytic activity. Additionally, the catalytic activity of Fe₂Mn and Fe₂Co connected through 3,3′,5,5′-azobenzenetetracarboxylate linker to form Fe₂M–PCN–Fe₂M is explored. Compared with Fe₂Mn–PCN–Fe₂Mn, Fe₂Co–PCN–Fe₂Co, and isolated Fe₂M clusters, the mixed-metal Fe₂Co–PCN–Fe₂Mn possesses excellent bifunctional catalytic activity, and the values of potential gap on the Mn and Co sites of Fe₂Co–PCN–Fe₂Mn are 0.69 and 0.70 V, respectively. Furthermore, the analysis of the electron structure indicates that constructing a mixed-metal cluster can efficiently enhance the electronic properties of the catalyst. In conclusion, the mixed-metal cluster strategy provides a new approach to further design and synthesize high-efficiency bifunctional electrocatalysts.

Graphical abstract

Keywords

bimetallic metal–organic frameworks / bifunctional electrocatalyst / density functional theory / oxygen reduction reaction / oxygen evolution reaction

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Acknowledgements

This work was supported by the Science and Technology Project of Sichuan Province (Grant No. 2022YFS0447), the Local Science and Technology Development Fund Projects Guided by the Central Government of China (Grant No. 2021ZYD0060), the Science and Technology Project of Southwest Petroleum University (Grant No. 2021JBGS03), the Special Project of Science and Technology Strategic Cooperation between Nanchong City and Southwest Petroleum University (Grant No. SXQHJH064), and the Postgraduate Research and Innovation Fund of Southwest Petroleum University (Grant No. 2021CXYB14). We acknowledge the National Supercomputing Center in Shenzhen for providing the computational resources and Materials Studio.

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://dx.doi.org/10.1007/s11705-022-2247-y and is accessible for authorized users.

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